The present invention relates generally to computers, and more specifically to lossless compression of data with high nominal ranges.
One example of high nominal-range data is floating-point data. An example of floating-point data that benefits from data compression is seismic data. Seismic processing involves the acquisition and analysis of fields of subsurface data, acquired through reflective seismic waves. With improvements in acquisition modalities, the amount of data to be stored and processed is increasing at a rapid rate. An example data field may be terabytes in size and may need to be stored for several months for analysis. The large size of such fields imply a large cost for transmission and storage, as well as computational costs during analysis since the data has to be moved to and from computational cores. Compression of seismic data can mitigate these costs, and the ability to achieve a high level of compression is of great interest in this area. Seismic data tends to be floating-point data, and is typically required to be compressed using lossless compression techniques so that information that may be of use during analysis is not discarded during compression.